Abstract
It has always been a rather tough task to communicate with someone possessing a hearing impairment. One of the most tested ways to establish such a communication is through the use of sign based languages. However, not many people are aware of the smaller intricacies involved with sign language. Sign language recognition using computer vision aims at eliminating the communication barrier between deaf-mute and ordinary people so that they can properly communicate with others. Recently the pandemic has left the whole world shaken up and has transformed the way we communicate. Video meetings have become essential for everyone, even people with a hearing disability. In recent studies, it has been found that people with hearing disabilities prefer to sign over typing during these video calls. In this paper, we are proposing a browser extension that will automatically translate sign language to subtitles for everyone else in the video call. The Large-scale dataset which contains more than 2000 Word-Level ASL videos, which were performed by over 100 signers will be used.
Abstract (translated)
与听障人士沟通一直是一项相当艰巨的任务。建立这种沟通的最常见方式之一是使用基于手势的语言（手语）。然而，许多人并不了解手语中包含的一些细微差别。计算机视觉中的手语识别技术旨在消除聋哑人和普通人之间的交流障碍，使他们能够更好地与其他人群进行沟通。 最近，疫情让全世界都受到了冲击，并且改变了我们的交流方式。视频会议已成为每个人的必需品，即使对于有听觉障碍的人也不例外。近期的研究表明，在这些视频通话中，听力受损的人更倾向于使用手语而不是打字。在这篇论文中，我们提出了一种浏览器扩展程序，该程序将自动把手语翻译成字幕供视频通话中的其他人观看。 为此，我们将采用一个大型数据集，其中包含超过2000个单词级别的ASL（美国手语）视频，这些视频由100多名手势使用者完成。
URL
https://arxiv.org/abs/2507.14543
